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Data Engineering with Databricks
What do you like best about the product?
I like Databricks because it provides all the elements necessary for mass data processing, the different components (notebook, cluster, jobs) are very well integrated and quite easy to use. A lot of training is offered to understand in depth the possibilities offered in Databricks, which makes it much easier to use.
What do you dislike about the product?
The Dashboard part integrated into Databricks is quite limited and does not allow the creation of complex and relevant dashboards
What problems is the product solving and how is that benefiting you?
Databricks solves the problem of scalability, it's easy to manage a large amount of data as a smaller one.
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Databricks for data world
What do you like best about the product?
It provides some key features like workspace, notebook, Apache spark, Delta Lake, and Scalability. It provides a centralized environment where teams can collaborate. We can work on Jupyter Notebook with Apache Spark which provides the engine that powers all processing of dataset. It provides Cross-team collaboration so engineers, analysts, scientists, and ML engineers can work seamlessly on the same platform. It also provides consistency with notebooks, users can transition between tasks and programming languages without the need for context-switching.
What do you dislike about the product?
In this Databricks platform, we can't migrate a library from the dev workspace to the prod workspace.
What problems is the product solving and how is that benefiting you?
It provide some key features like workspace, notebook, Apache spark, Delta Lake and Scalability.
It provide centralized evn where team can collaborate.
We can work on jupyter notebook with Apache spark which provide engine that power all processing of dataset.
It provide Cross-team collaboration so enengineers, analysts, scientists and ML engineers can work seamlessly in the same platform.
Consistency: with notebooks, users can transition between tasks and programming languages without the need for context-switching.
It provide centralized evn where team can collaborate.
We can work on jupyter notebook with Apache spark which provide engine that power all processing of dataset.
It provide Cross-team collaboration so enengineers, analysts, scientists and ML engineers can work seamlessly in the same platform.
Consistency: with notebooks, users can transition between tasks and programming languages without the need for context-switching.
One stop solution for all Data need
What do you like best about the product?
Databricks provides multiple language support as well as a well guided UI for all the processing needs. Moreover it has in-built diagnose of error which helps debugging and save time. It has also a well guided Documentation available.
We can implement data engineering work loads as well as data science workloads so it can help one organisation frequently changing domains. It also has wide integration with all cloud providers and legacy systems. Having any explicit issues can be resolved with Customer support available readily.
We can implement data engineering work loads as well as data science workloads so it can help one organisation frequently changing domains. It also has wide integration with all cloud providers and legacy systems. Having any explicit issues can be resolved with Customer support available readily.
What do you dislike about the product?
Having prior cloud account can be an issue sometimes. Understanding its workflow can sometimes be a challenge to users.
What problems is the product solving and how is that benefiting you?
Having all integrations at one place helps saving time, resources and cost. Providing scalability to all resources helps saving efforts.
Databricks Review
What do you like best about the product?
I like to use it for creating my ETL Pipelines. Its features helps us to make the data transformation so easy.
What do you dislike about the product?
There is nothing to dislike as of now. It is best as it is.
What problems is the product solving and how is that benefiting you?
It helps us in creating and maintaining the ETL Pipelines. The data transformation features are very useful to have in the pipelines. Its data security and integrity is very useful for maintaing a healthy pipeline.
Decent platform
What do you like best about the product?
I like that a lot of components are built so you just need to use or manage it
What do you dislike about the product?
I dont like that i cant install driver and items on clusters to be used by multiple users
I also dont like that a lot of the GEN AI items (transformers, hosting own models, fine-tuning) doesnt work with the given examples from databricks
- makes something simple take weeks to develop
I also dont like that a lot of the GEN AI items (transformers, hosting own models, fine-tuning) doesnt work with the given examples from databricks
- makes something simple take weeks to develop
What problems is the product solving and how is that benefiting you?
LLM, Model development
Helps to use it. But doesnt really add the performance capacity when the DS arent using spark apis
Helps to use it. But doesnt really add the performance capacity when the DS arent using spark apis
ETL developpement on the Databricks Data Intelligence Platform
What do you like best about the product?
Simple of use. One unique point of truth and of work. Very easy governance and very convenient and secure way of sharing the data, which is one of the biggest issue in the industry
What do you dislike about the product?
Not especially easy to handle at first, at least for the data engineering, real time streaming part.
What problems is the product solving and how is that benefiting you?
Real time streaming processing of the data, and secure data sharing
These have been complicated to set up with other technologies, and is greatly simplified with Databricks.
Moreover the automated governance that is provided is greatly beneficial.
These have been complicated to set up with other technologies, and is greatly simplified with Databricks.
Moreover the automated governance that is provided is greatly beneficial.
Complete unified platform for Data Enginnering and ML workloads in the era of AI.
What do you like best about the product?
What I appreciate most about Databricks Data Intelligence Platform is its seamless integration of data engineering, data science, and collaboration features. Its unified environment empowers teams to effortlessly collaborate on data-driven projects, accelerating innovation and enabling organizations to derive actionable insights from their data with ease and efficiency.
What do you dislike about the product?
Higher compute cost, missing data sharing feature similar to what we have in Snowflake
What problems is the product solving and how is that benefiting you?
Massive data Processing , I believe at present only Databricks is capable to process this great amount of data.
Databricks Review.
What do you like best about the product?
The best thing is I can choose any cloud provider for my infrastructure. The interactive environment called Notebooks which allows to write and execute codes is very easy to use. The magic commands are very much helpful. The UI is good and interactive.
What do you dislike about the product?
Nothing as of now but there can be more features added.
What problems is the product solving and how is that benefiting you?
I can choose between Single node and Multi node clutser according to our requirement which solves our problem. I can create workflows easily by connecting it to the notebooks and can also mention external parameters. Spot instances are very much cost saving. And the feature called Photon which helps in fast query performance at low cost.
Great product for data engineering - playing with data gets easy.
What do you like best about the product?
Creation of data product with databricks gets easy. we can easily deliver our product to the clients on time.
Data ingeston and data curation with great performance makes the work easy.
cost effective- Launching of clusters and gets stop after work save much cost as using other data performance tools.
Understandable architecture with a sequence helps to manage the tool.
Customer support is awesome , they helps to solve all the issues i faced.
Integration and setup of databricks using terraform helps alot to manage the workspace .
Data ingeston and data curation with great performance makes the work easy.
cost effective- Launching of clusters and gets stop after work save much cost as using other data performance tools.
Understandable architecture with a sequence helps to manage the tool.
Customer support is awesome , they helps to solve all the issues i faced.
Integration and setup of databricks using terraform helps alot to manage the workspace .
What do you dislike about the product?
It took much amount of time to restart a cluster . This should be improved.
What problems is the product solving and how is that benefiting you?
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Databricks is seriously good stuff
What do you like best about the product?
Date of breakfast well integrated and crafted suite of applications making a harmonious environment for all kinds of data, data warehouse and applications.
What do you dislike about the product?
Sometimes things are not as smooth and easy as you wish but principally because features still in progress of improvements and discovery. I actually often find the shortcoming today is a naturally smooth add to the suite after the next release
What problems is the product solving and how is that benefiting you?
The common ones you are most looking for help with, velocity variety, column, and veracity. Made best and easiest with a thoughtfully integrated and crafted singular platform.
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